Stat133_lab02
# remove existing objects
rm(list = ls())# download RData file into your working directory
rdata <- "https://github.com/ucb-stat133/stat133-labs/raw/master/data/nba2018-salary-points.RData"
download.file(url = rdata, destfile = 'nba2018-salary-points.RData')# load data in your R session
load('nba2018-salary-points.RData')# list the available objects with ls()
ls()## [1] "age" "experience" "player" "points1" "points2"
## [6] "points3" "position" "rdata" "salary" "scored"
## [11] "team"four <- head(player, n = 4)
# number one#
four[1]## [1] "Al Horford"# an index of zero:#
four[0]## character(0)#a negative index: #
four[-1]## [1] "Amir Johnson" "Avery Bradley" "Demetrius Jackson"#various negative indices: #
four[-c(1,2,3)]## [1] "Demetrius Jackson"#an index greater than the length of the vector: #
four[5]## [1] NA#repeated indices: #
four[c(1,2,2,3,3,3)]## [1] "Al Horford" "Amir Johnson" "Amir Johnson" "Avery Bradley"
## [5] "Avery Bradley" "Avery Bradley"Figure out how to use seq(), rep(), and bracket notation, to extract:
all the even elements in player
all the odd elements in salary
all multiples of 5 (e.g. 5, 10, 15, etc) of team
elements in positions 10, 20, 30, 40, etc of scored
all the even elements in team but this time in reverse order
player[seq(2, length(player), by = 2)]## [1] "Amir Johnson" "Demetrius Jackson"
## [3] "Isaiah Thomas" "James Young"
## [5] "Jonas Jerebko" "Kelly Olynyk"
## [7] "Terry Rozier" "Andrew Bogut"
## [9] "Dahntay Jones" "Derrick Williams"
## [11] "Iman Shumpert" "James Jones"
## [13] "Kay Felder" "Kyle Korver"
## [15] "Larry Sanders" "Richard Jefferson"
## [17] "Bruno Caboclo" "Delon Wright"
## [19] "DeMarre Carroll" "Jakob Poeltl"
## [21] "Kyle Lowry" "Norman Powell"
## [23] "Pascal Siakam" "Serge Ibaka"
## [25] "Bradley Beal" "Chris McCullough"
## [27] "Danuel House" "Jason Smith"
## [29] "Kelly Oubre" "Markieff Morris"
## [31] "Tomas Satoransky" "DeAndre' Bembry"
## [33] "Dwight Howard" "Gary Neal"
## [35] "Kent Bazemore" "Lamar Patterson"
## [37] "Mike Dunleavy" "Paul Millsap"
## [39] "Taurean Waller-Prince" "Tim Hardaway"
## [41] "Gary Payton" "Greg Monroe"
## [43] "Jason Terry" "Khris Middleton"
## [45] "Matthew Dellavedova" "Miles Plumlee"
## [47] "Rashad Vaughn" "Steve Novak"
## [49] "Thon Maker" "Aaron Brooks"
## [51] "C.J. Miles" "Glenn Robinson"
## [53] "Joe Young" "Lance Stephenson"
## [55] "Monta Ellis" "Paul George"
## [57] "Rodney Stuckey" "Anthony Morrow"
## [59] "Cameron Payne" "Denzel Valentine"
## [61] "Isaiah Canaan" "Jimmy Butler"
## [63] "Michael Carter-Williams" "Paul Zipser"
## [65] "Rajon Rondo" "Dion Waiters"
## [67] "Hassan Whiteside" "Josh McRoberts"
## [69] "Justise Winslow" "Okaro White"
## [71] "Tyler Johnson" "Wayne Ellington"
## [73] "Andre Drummond" "Beno Udrih"
## [75] "Darrun Hilliard" "Ish Smith"
## [77] "Kentavious Caldwell-Pope" "Michael Gbinije"
## [79] "Reggie Jackson" "Tobias Harris"
## [81] "Brian Roberts" "Christian Wood"
## [83] "Frank Kaminsky" "Johnny O'Bryant"
## [85] "Marco Belinelli" "Michael Kidd-Gilchrist"
## [87] "Nicolas Batum" "Treveon Graham"
## [89] "Chasson Randle" "Derrick Rose"
## [91] "Justin Holiday" "Kyle O'Quinn"
## [93] "Marshall Plumlee" "Mindaugas Kuzminskas"
## [95] "Sasha Vujacic" "Aaron Gordon"
## [97] "Arinze Onuaku" "C.J. Watson"
## [99] "D.J. Augustin" "Elfrid Payton"
## [101] "Jeff Green" "Marcus Georges-Hunt"
## [103] "Nikola Vucevic" "Stephen Zimmerman"
## [105] "Alex Poythress" "Gerald Henderson"
## [107] "Jahlil Okafor" "Joel Embiid"
## [109] "Justin Harper" "Richaun Holmes"
## [111] "Sergio Rodriguez" "T.J. McConnell"
## [113] "Timothe Luwawu-Cabarrot" "Anthony Bennett"
## [115] "Brook Lopez" "Greivis Vasquez"
## [117] "Jeremy Lin" "Justin Hamilton"
## [119] "Luis Scola" "Randy Foye"
## [121] "Sean Kilpatrick" "Trevor Booker"
## [123] "Anderson Varejao" "Damian Jones"
## [125] "Draymond Green" "James Michael McAdoo"
## [127] "Kevin Durant" "Klay Thompson"
## [129] "Patrick McCaw" "Stephen Curry"
## [131] "Bryn Forbes" "David Lee"
## [133] "Dejounte Murray" "Joel Anthony"
## [135] "Kawhi Leonard" "LaMarcus Aldridge"
## [137] "Nicolas Laprovittola" "Pau Gasol"
## [139] "Bobby Brown" "Clint Capela"
## [141] "Isaiah Taylor" "Lou Williams"
## [143] "Nene Hilario" "Ryan Anderson"
## [145] "Trevor Ariza" "Alan Anderson"
## [147] "Blake Griffin" "Brice Johnson"
## [149] "DeAndre Jordan" "J.J. Redick"
## [151] "Luc Mbah a Moute" "Paul Pierce"
## [153] "Wesley Johnson" "Boris Diaw"
## [155] "Derrick Favors" "Gordon Hayward"
## [157] "Joe Ingles" "Joel Bolomboy"
## [159] "Rodney Hood" "Shelvin Mack"
## [161] "Alex Abrines" "Domantas Sabonis"
## [163] "Enes Kanter" "Josh Huestis"
## [165] "Nick Collison" "Russell Westbrook"
## [167] "Steven Adams" "Victor Oladipo"
## [169] "Brandan Wright" "Deyonta Davis"
## [171] "JaMychal Green" "Marc Gasol"
## [173] "Toney Douglas" "Troy Daniels"
## [175] "Wade Baldwin" "Zach Randolph"
## [177] "Allen Crabbe" "Damian Lillard"
## [179] "Evan Turner" "Jusuf Nurkic"
## [181] "Meyers Leonard" "Pat Connaughton"
## [183] "Alonzo Gee" "Darrell Arthur"
## [185] "Gary Harris" "Jameer Nelson"
## [187] "Juan Hernangomez" "Malik Beasley"
## [189] "Mike Miller" "Roy Hibbert"
## [191] "Wilson Chandler" "Anthony Davis"
## [193] "Dante Cunningham" "Donatas Motiejunas"
## [195] "Jarrett Jack" "Jrue Holiday"
## [197] "Omri Casspi" "Reggie Williams"
## [199] "Tim Frazier" "Ben Bentil"
## [201] "Devin Harris" "Dorian Finney-Smith"
## [203] "Harrison Barnes" "Jarrod Uthoff"
## [205] "Manny Harris" "Nicolas Brussino"
## [207] "Salah Mejri" "Wesley Matthews"
## [209] "Arron Afflalo" "Buddy Hield"
## [211] "Garrett Temple" "Jordan Farmar"
## [213] "Langston Galloway" "Rudy Gay"
## [215] "Ty Lawson" "Willie Cauley-Stein"
## [217] "Andrew Wiggins" "Cole Aldrich"
## [219] "John Lucas III" "Karl-Anthony Towns"
## [221] "Nemanja Bjelica" "Shabazz Muhammad"
## [223] "Zach LaVine" "Corey Brewer"
## [225] "David Nwaba" "Jordan Clarkson"
## [227] "Luol Deng" "Nick Young"
## [229] "Thomas Robinson" "Tyler Ennis"
## [231] "Alex Len" "Derrick Jones"
## [233] "Dragan Bender" "Eric Bledsoe"
## [235] "Jarell Eddie" "Leandro Barbosa"
## [237] "Ronnie Price" "Tyler Ulis"salary[seq(1, length(player), by = 2)]## [1] 26540100 8269663 1410598 6286408 4743000 1223653 3578880
## [8] 8000000 7806971 259626 5145 12800000 874636 21165675
## [15] 17638063 30963450 15330435 7330000 26540100 543471 14382022
## [22] 1921320 5300000 6050000 3730653 1200000 543471 15944154
## [29] 16957900 12000000 5893981 3386598 2708582 8400000 392478
## [36] 4000000 2500000 1015696 418228 3850000 51449 2995421
## [43] 5374320 12517606 925000 1403611 10500000 6348759 236457
## [50] 2368327 10230179 650000 8800000 1800000 4000000 2463840
## [57] 1052342 14153652 1453680 874636 23200000 1643040 1709720
## [64] 5782450 425000 13219250 15890000 4000000 874636 1227000
## [71] 543471 4000000 1015696 6500000 7000000 1704120 10991957
## [78] 4625000 2255644 2969880 375579 231521 5318313 6511628
## [85] 12000000 12250000 138938 6000000 24559380 11242000 17000000
## [92] 4317720 6191000 543471 543471 1375000 51449 17000000
## [99] 1209680 980431 17000000 6540000 3909840 31969 10000000
## [106] 2318280 442126 9424084 1514160 2993040 1015696 96969
## [113] 8550000 6088993 194494 1562280 1074145 980431 3333333
## [120] 1914544 1395600 726672 202300 11131368 1551659 1015696
## [127] 1403611 1182840 383351 5782450 2898000 10000000 543471
## [134] 2898000 874636 1192080 14000000 3578948 14445313 543471
## [141] 12385364 26540100 1045000 6000000 1720560 181969 11000000
## [148] 1551659 22868827 543471 13253012 1403611 1551659 10154495
## [155] 3940320 8000000 1015696 11000000 937800 2121288 2340600
## [162] 2183072 2483040 980431 4837500 247991 543471 8950000
## [169] 945000 22116750 2898000 1286160 26540100 5505618 4264057
## [176] 83119 7680965 3219579 6666667 600000 8988764 2751360
## [183] 1350120 15050000 3241800 3210840 150000 12078652 2328530
## [190] 1358500 3533333 4600000 543471 16957900 8081363 234915
## [197] 9904494 79922 11241218 650000 1015696 25000000 8375000
## [204] 4096950 680937 4384490 105498 2898000 8000000 4008882
## [211] 5229454 2202240 8046500 1439880 1188840 10661286 2022240
## [218] 3500000 2348783 3911380 3872520 13550000 1339680 5281680
## [225] 5332800 1034956 3267120 1551659 6191000 16000000 874636
## [232] 12606250 2223600 23069 10470000 469841 2941440 2128920
## [239] 12415000team[seq(5, length(player), by = 5)]## [1] BOS BOS BOS CLE CLE CLE TOR TOR TOR WAS WAS WAS ATL ATL ATL ATL MIL
## [18] MIL MIL IND IND IND IND CHI CHI CHI MIA MIA MIA DET DET DET CHO CHO
## [35] CHO NYK NYK NYK ORL ORL ORL PHI PHI PHI PHI BRK BRK BRK BRK GSW GSW
## [52] GSW SAS SAS SAS HOU HOU HOU LAC LAC LAC UTA UTA UTA OKC OKC OKC MEM
## [69] MEM MEM POR POR POR DEN DEN DEN NOP NOP NOP DAL DAL DAL DAL SAC SAC
## [86] SAC MIN MIN MIN LAL LAL LAL PHO PHO PHO
## 30 Levels: ATL BOS BRK CHI CHO CLE DAL DEN DET GSW HOU IND LAC LAL ... WASscored[seq(10, length(player), by = 10)]## [1] 299 156 4 165 1779 1063 801 1143 577 322 630 291 538 98
## [15] 127 1321 780 1154 124 1046 64 559 1539 357 776 1999 1888 818
## [29] 936 1173 476 430 33 58 106 304 851 4 6 0 8 378
## [43] 681 2061 120 170 24rev(team[seq(2, length(player), by = 2)])## [1] PHO PHO PHO PHO PHO PHO PHO PHO LAL LAL LAL LAL LAL LAL LAL MIN MIN
## [18] MIN MIN MIN MIN MIN SAC SAC SAC SAC SAC SAC SAC SAC DAL DAL DAL DAL
## [35] DAL DAL DAL DAL DAL NOP NOP NOP NOP NOP NOP NOP NOP DEN DEN DEN DEN
## [52] DEN DEN DEN DEN DEN POR POR POR POR POR POR MEM MEM MEM MEM MEM MEM
## [69] MEM MEM OKC OKC OKC OKC OKC OKC OKC OKC UTA UTA UTA UTA UTA UTA UTA
## [86] LAC LAC LAC LAC LAC LAC LAC LAC HOU HOU HOU HOU HOU HOU HOU SAS SAS
## [103] SAS SAS SAS SAS SAS SAS GSW GSW GSW GSW GSW GSW GSW GSW BRK BRK BRK
## [120] BRK BRK BRK BRK BRK BRK PHI PHI PHI PHI PHI PHI PHI PHI PHI ORL ORL
## [137] ORL ORL ORL ORL ORL ORL ORL NYK NYK NYK NYK NYK NYK NYK CHO CHO CHO
## [154] CHO CHO CHO CHO CHO DET DET DET DET DET DET DET DET MIA MIA MIA MIA
## [171] MIA MIA MIA CHI CHI CHI CHI CHI CHI CHI CHI IND IND IND IND IND IND
## [188] IND IND MIL MIL MIL MIL MIL MIL MIL MIL MIL ATL ATL ATL ATL ATL ATL
## [205] ATL ATL ATL WAS WAS WAS WAS WAS WAS WAS TOR TOR TOR TOR TOR TOR TOR
## [222] TOR CLE CLE CLE CLE CLE CLE CLE CLE CLE BOS BOS BOS BOS BOS BOS BOS
## 30 Levels: ATL BOS BRK CHI CHO CLE DAL DEN DET GSW HOU IND LAC LAL ... WASLogical Subsetting and Comparisons
scored_four <- scored[1:4]
# elements greater than 100
scored_four[scored_four > 100]## [1] 952 520 894# elements less than 100
scored_four[scored_four < 100]## [1] 10# elements less than or equal to 10
scored_four[scored_four <= 10]## [1] 10# elements different from 10
scored_four[scored_four != 10]## [1] 952 520 894TRUE & TRUE## [1] TRUETRUE & FALSE## [1] FALSEFALSE & FALSE## [1] FALSE# OR
TRUE | TRUE## [1] TRUETRUE | FALSE## [1] TRUEFALSE | FALSE## [1] FALSE# NOT
!TRUE## [1] FALSE!FALSE## [1] TRUE# players of Golden State (GSW)
player[team == 'GSW']## [1] "Anderson Varejao" "Andre Iguodala" "Damian Jones"
## [4] "David West" "Draymond Green" "Ian Clark"
## [7] "James Michael McAdoo" "JaVale McGee" "Kevin Durant"
## [10] "Kevon Looney" "Klay Thompson" "Matt Barnes"
## [13] "Patrick McCaw" "Shaun Livingston" "Stephen Curry"
## [16] "Zaza Pachulia"# name of players with salaries greater than 20 million dollars
player[salary > 20000000]## [1] "Al Horford" "Kevin Love" "LeBron James"
## [4] "DeMar DeRozan" "Bradley Beal" "Dwight Howard"
## [7] "Paul Millsap" "Dwyane Wade" "Hassan Whiteside"
## [10] "Andre Drummond" "Nicolas Batum" "Carmelo Anthony"
## [13] "Derrick Rose" "Brook Lopez" "Kevin Durant"
## [16] "LaMarcus Aldridge" "James Harden" "Blake Griffin"
## [19] "Chris Paul" "DeAndre Jordan" "Russell Westbrook"
## [22] "Chandler Parsons" "Marc Gasol" "Mike Conley"
## [25] "Damian Lillard" "Anthony Davis" "Dirk Nowitzki"
## [28] "Harrison Barnes"# name of players with scored points between 1000 and 1200 (exclusive)
player[scored > 1000 & scored < 1200]## [1] "Kevin Love" "Markieff Morris"
## [3] "Otto Porter" "Dwight Howard"
## [5] "Tim Hardaway" "Jabari Parker"
## [7] "Myles Turner" "Dwyane Wade"
## [9] "Tyler Johnson" "Andre Drummond"
## [11] "Kentavious Caldwell-Pope" "Marcus Morris"
## [13] "Nicolas Batum" "Derrick Rose"
## [15] "Kristaps Porzingis" "Aaron Gordon"
## [17] "Elfrid Payton" "Evan Fournier"
## [19] "Nikola Vucevic" "Dario Saric"
## [21] "Chris Paul" "DeAndre Jordan"
## [23] "J.J. Redick" "Jamal Crawford"
## [25] "Rudy Gobert" "Enes Kanter"
## [27] "Victor Oladipo" "Zach Randolph"
## [29] "Danilo Gallinari" "Wilson Chandler"
## [31] "Jrue Holiday"Write commands, using bracket notation, to answer the following questions (you may need to use min(), max(), which(), which.min(), which.max()):
#players in position Center, of Warriors (GSW)
player[position == "C" & team == "GSW"]## [1] "Anderson Varejao" "Damian Jones" "David West"
## [4] "JaVale McGee" "Kevon Looney" "Zaza Pachulia"#players of both GSW (warriors) and LAL (lakers)
player[team == 'GSW' | team == 'LAL']## [1] "Anderson Varejao" "Andre Iguodala" "Damian Jones"
## [4] "David West" "Draymond Green" "Ian Clark"
## [7] "James Michael McAdoo" "JaVale McGee" "Kevin Durant"
## [10] "Kevon Looney" "Klay Thompson" "Matt Barnes"
## [13] "Patrick McCaw" "Shaun Livingston" "Stephen Curry"
## [16] "Zaza Pachulia" "Brandon Ingram" "Corey Brewer"
## [19] "D'Angelo Russell" "David Nwaba" "Ivica Zubac"
## [22] "Jordan Clarkson" "Julius Randle" "Luol Deng"
## [25] "Metta World Peace" "Nick Young" "Tarik Black"
## [28] "Thomas Robinson" "Timofey Mozgov" "Tyler Ennis"# players in positions Shooting Guard and Point Guards, of Lakers (LAL)
player[team == 'LAL' & (position == 'SG' | position == 'PG')]## [1] "D'Angelo Russell" "David Nwaba" "Jordan Clarkson"
## [4] "Nick Young" "Tyler Ennis"# subset Small Forwards of GSW and LAL
player[position == 'SF' & (team == 'GSW' | team == 'LAL')]## [1] "Andre Iguodala" "Matt Barnes" "Brandon Ingram"
## [4] "Corey Brewer" "Luol Deng" "Metta World Peace"# name of the player with largest salary
player[which.max(salary)]## [1] "LeBron James"# name of the player with smallest salary
player[which.min(salary)]## [1] "Edy Tavares"# name of the player with largest number of scored points
player[which.max(scored)]## [1] "Russell Westbrook"# salary of the player with largest number of scored points
salary[which.max(scored)]## [1] 26540100# largest salary of all Centers
max(salary[position == 'C'])## [1] 26540100# team of the player with the largest number of scored points
team[which.max(scored)]## [1] OKC
## 30 Levels: ATL BOS BRK CHI CHO CLE DAL DEN DET GSW HOU IND LAC LAL ... WAS# name of the player with the largest number of 3-pointers
player[which.max(points3)]## [1] "Stephen Curry"Subsetting with Character Vectors
plot(scored, salary)
library(plotly)## Loading required package: ggplot2## Warning: package 'ggplot2' was built under R version 3.4.4##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layoutplot_ly(x = scored, y = salary, type = "scatter", mode = "markers")## Warning: package 'bindrcpp' was built under R version 3.4.4log_scored <- log(scored)
log_salary <- log(salary)
plot(log_scored, log_salary)
plot(log_scored, log_salary)
text(log_scored, log_salary, labels = player)
plot(log_scored, log_salary)
text(log_scored, log_salary, labels = abbreviate(player))
# Your Turn: create a scatterplot of points and salary for the Warriors (GSW), displaying the names of the players. Generate two scatterplots, one with raw values (original scale, and another plot with log-transformations).
plot(x = scored[team == "GSW"], y = salary[team == "GSW"])
text(scored[team == "GSW"], salary[team == "GSW"], labels = player[team == "GSW"])
plot(x = log(scored[team == "GSW"]), y = log(salary[team == "GSW"]))
text(log(scored[team == "GSW"]), log(salary[team == "GSW"]), labels = player[team == "GSW"])
Factors
is.factor(team)## [1] TRUEposition_fac <- factor(position)
table(position_fac)## position_fac
## C PF PG SF SG
## 97 98 96 84 102position_fac[1:5]## [1] C PF SG PG SF
## Levels: C PF PG SF SG# positions of Warriors
position_fac[team == 'GSW']## [1] C SF C C PF SG PF C PF C SG SF SG PG PG C
## Levels: C PF PG SF SG# positions of players with salaries > 15 millions
position_fac[salary > 15000000]## [1] C PF PG SF C SG SG C PG C SF PF C SF SF SG SF PG C C PF SG SF
## [24] PG C C SG C PF PF SG SF PF C PG PF PF PG C SF C PG SF C PG SG
## [47] PG SF SF C C PF PF SG SF C
## Levels: C PF PG SF SG# frequencies (counts) of positions with salaries > 15 millions: use table
table(position_fac[salary > 15000000])##
## C PF PG SF SG
## 17 10 9 12 8# relative frequencies (proportions) of 'SG' (Shooting Guards) in each team
prop.table(table(team[position_fac == 'SG']))##
## ATL BOS BRK CHI CHO CLE
## 0.02941176 0.02941176 0.03921569 0.04901961 0.04901961 0.03921569
## DAL DEN DET GSW HOU IND
## 0.03921569 0.03921569 0.02941176 0.02941176 0.02941176 0.01960784
## LAC LAL MEM MIA MIL MIN
## 0.02941176 0.02941176 0.02941176 0.03921569 0.03921569 0.01960784
## NOP NYK OKC ORL PHI PHO
## 0.01960784 0.03921569 0.01960784 0.04901961 0.02941176 0.04901961
## POR SAC SAS TOR UTA WAS
## 0.02941176 0.04901961 0.03921569 0.01960784 0.01960784 0.02941176plot(scored, salary, col= position_fac, pch = 25, cex = 2, xlab= "Scores", ylab = "Salary")